Data Engineer

Location: Herndon, VA

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  • Bachelor’s Degree in Computer Science, Information Systems, Data Analytics, or related technical/engineering field
  • 3+ years Structured Query Language (SQL) experience
  • 2+ years of experience with Python or other relevant scripting language
  • 2+ years of experience with data warehouse technical architecture, infrastructure components, and extract, transform, load (ETL) procedure
  • 1+ years of experience with the AWS tech stack – Glue, Redshift, EMR, S3, EC2, and Lambda will be used regularly in this role
  • 1+ years of experience with Data Architecture and Design
  • 1+ years of experience in preparing data for direct use in visualization tools, such as Salesforce, Tableau, or Amazon QuickSight
Amazon is looking for a highly analytical Data Engineer to join the AWS Data Center Engineering team. The Data Center Engineering team owns the availability of AWS data centers, and has a direct impact on the customer experience. We obsess over customers by developing the most advanced engineering solutions that result in world class uptime, while continuously reducing costs for our customers. Amazon offers a fast paced, fun, and exciting work environment. We continue to grow at exponential rates and are looking for individuals that can support our speed to market, enjoy a challenge, and have a desire for professional growth and continuous learning experiences.

As a Data Engineer, you will partner with Business Intelligence Engineers and partner teams to build data pipelines and solutions to harness the vast amount of operational data from the AWS fleet. You will own the timely delivery of such data for use in downstream business intelligence solutions, as well as all necessary actions to ensure the reliability of data provided for business decision making. Data analysis is at the core Amazon’s culture, and your work will have a direct impact on decision making and strategy for our organization.

The ideal candidates will have excellent analytical abilities, intense curiosity, and strong technical skills. They will have a strong bias toward data driven decision making, and building scalable data pipelines and systems to facilitate such decision making. They will be a self-starter; comfortable with ambiguity; able to think big and be creative, while exercising strong judgment and good instincts to be right a lot. The ideal candidate is motivated by delivering high-quality and innovative solutions within timeframes that most think are impossible. If you are excited about using data to look around corners and drive engineering solutions that are the foundation of AWS data centers, this role is for you!

  • Collaborate with Business Intelligence Engineering team members, engineering stakeholders, partner technical teams, and business stakeholders, to gather business and functional requirements, and translate these requirements into a robust, scalable, and operable data infrastructure that works well within the overall AWS data architecture, and leads to improved engineering decisions.
  • Develop a deep understanding and awareness of operational data from the AWS fleet, and build mechanisms for retrieving and aggregating such data for use by downstream business intelligence solutions.
  • Develop a deep understanding of our vast data sources, and provide continuous recommendations for use to solve specific business problems.
  • Take ownership of data reliability by, among other things, performing deep-dives to find root causes of potential data anomalies, and taking subsequent action to address these anomalies.
  • Continuously optimize the performance of data queries, and address extract, transform, load (ETL) procedures.
  • Insist on the highest standards by recognizing and adopting best practices in reporting and analysis: data integrity, test design, analysis, validation, and documentation.
  • Expert-level knowledge of SQL
  • Proficient in Scala/Spark/Hadoop
  • Experience in documenting technical/data systems for technical and business leaders
  • Experience working with data scientists on research and machine learning problems
  • Be self-driven, detail-oriented, and show ability to deliver on ambiguous projects with incomplete or dirty data
  • Meets/exceeds Amazon’s leadership principles requirements for this role
  • Meets/exceeds Amazon’s functional/technical depth and complexity for this role
Amazon is committed to a diverse and inclusive workforce. Amazon is an equal opportunity employer and does not discriminate on the basis of race, ethnicity, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit

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